Bazinga! Caracterizando e Detectando Sarcasmo e Ironia no Twitter

  • Pollyanna Gonçalves Universidade Federal de Minas Gerais
  • Daniel Dalip Universidade Federal de Minas Gerais
  • Julio Reis Universidade Federal de Minas Gerais
  • Johnnatan Messias Universidade Federal de Minas Gerais
  • Filipe Ribeiro Universidade Federal de Ouro Preto
  • Philipe Melo Universidade Federal de Minas Gerais
  • Leandro Araújo Universidade Federal de Minas Gerais
  • Marcos Gonçalves Universidade Federal de Minas Gerais
  • Fabricio Benevenuto Universidade Federal de Minas Gerais

Resumo


Sarcasmo e ironia são formas de discurso muito utilizadas dentro e fora da Web, tendo o poder de transformar características como polaridade ou sentido de uma sentença. Ser capaz de caracterizar e detectar mensagens sarcásticas ou irônicas em dados coletados da Web pode aprimorar diversos sistemas de tomada de decisão baseados em Processamento de Linguagem Natural (PLN) como a tarefa de análise de sentimentos, sumarização de textos e sistemas de ranqueamento de reviews. Nesse trabalho, propomos diversas abordagens para a caracterização e posterior classificação de sarcasmo e ironia em mensagens postadas na rede social online Twitter. Utilizando uma base automaticamente coletada de tweets com as hashtags #sarcasm" e "#irony", e usando uma larga gama de técnicas de caracterização e classificação, nossos resultados de detecção alcançaram taxas satisfatórias de acurácia e Macro-F1."

Palavras-chave: Detecção de Sarcasmo, Detecção de Ironia, Twitter

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Publicado
01/08/2015
GONÇALVES, Pollyanna et al. Bazinga! Caracterizando e Detectando Sarcasmo e Ironia no Twitter. In: BRAZILIAN WORKSHOP ON SOCIAL NETWORK ANALYSIS AND MINING (BRASNAM), 4. , 2015, Recife. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2015 . p.  . ISSN 2595-6094. DOI: https://doi.org/10.5753/brasnam.2015.6778.

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